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面向电网监测的无线传感器网络关键技术研究
引用本文:李婧,温蜜,薛梅.面向电网监测的无线传感器网络关键技术研究[J].上海电力学院学报,2017,33(4):367-371,384.
作者姓名:李婧  温蜜  薛梅
作者单位:上海电力学院 计算机科学与技术学院,上海电力学院 计算机科学与技术学院,上海电力学院 计算机科学与技术学院
基金项目:国家自然科学基金(61572310).
摘    要:电网监测的WSN中存在网络路由路径单一、负载不均衡、生命周期短和可维护性差等问题,因此引入局部压缩感知和低占空比机制对其网络性能进行优化.对面向电网监测的无线传感器网络中存在的关键技术进行了详细分析,并具体阐述了国内外对于该领域的研究现状及进展,提出针对局部压缩感知数据的有效恢复、低占空比机制中精确时间同步、电网监测环境下传感器网络的最优化配置等3个关键问题的研究,可以延长电网监测WSN的整体生存时间,为电网监测提供有Qo S保证的数据采集与传输,推动WSN在电力系统成功应用.

关 键 词:压缩感知  电网监测  无线传感器网络  低占空比
收稿时间:2017/3/9 0:00:00

Research on Key Technologies of Wireless Sensor Networks for Power Grid Monitoring
LI Jing,WEN Mi and XUE Mei.Research on Key Technologies of Wireless Sensor Networks for Power Grid Monitoring[J].Journal of Shanghai University of Electric Power,2017,33(4):367-371,384.
Authors:LI Jing  WEN Mi and XUE Mei
Affiliation:School of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 200090, China,School of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 200090, China and School of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 200090, China
Abstract:In the WSN of power grid system,there are many practical challenges in the designs of WSN,such as the limited choices of routing paths,imbalanced network traffic,limited life-time of WSN,and the complexity of maintenance.To address these challenges,it is proposed to investigate and optimize the performance of WSNs based on regional compressed sensing (RCS) and low-duty-cycle (LDC) mechanism.The key technologies of wireless sensor networks for grid monitoring are introduced.In addition,the research status and progress of this field at domestic and abroad are described in detail.Three key technologies are proposed including how to realize RCS so that we can reconstruct original data efficiently,how to improve the accuracy of clock synchronization and how to optimize the setting of WSN for real-time power-grid monitoring.With these research topics,it will increase life-time of WSN,supply efficient and QoS guaranteed data collection and translation and facilitate the deployment of smart grid system.
Keywords:compressed sensing  grid monitoring  wireless sensor network  low-duty-cycle
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